A Monte Carlo Methodology for Solving the Optimal Timber Harvest Problem with Stochastic Timber and Carbon Prices

Stanislav Petrasek, John Perez-Garcia


This article presents a Monte Carlo methodology for solving the
  stochastic optimal timber harvest problem modeled as a recurrent
  American call option. A detailed description of the proposed method-
  ology is given, and the Monte Carlo technique is contrasted with finite
  difference methods typically used to find solutions of the optimal har-
  vest problem with stochastic prices. The use of the methodology is
  then demonstrated via an example. In the example, expected bare
  land values and optimal harvest policies are calculated for a Douglas-
  fir stand in western Washington State. It is assumed that the forest
  owner derives revenue from traditional timber sales and carbon seques-
  tration, and that prices of timber and carbon follow a known stochastic
  process. Results of the calculations are discussed.  MCFNS 2(2):67-77.


Optimal Harvest; American Option; Monte Carlo; Carbon Sequestration

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